Target detection regression loss function 1: Comparison of L1 loss, L2 loss and Smooth L1 Loss

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Target detection regression loss function 1: Comparison of L1 loss, L2 loss and Smooth L1 Loss

smooth l1 loss & l1 loss & l2 loss

[Loss function] SmoothL1Loss Smooth L1 loss function

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[Machine Learning] Summary of Loss Function (2023 latest finishing) Keywords: Logistic, Hinge, Exponential, Modified Huber, Softmax, L1, L2 regularization

[Machine Learning Linear Regression] The inner product and L2 norm in the loss function

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[Target detection series] Detailed explanation of the loss function of yolov1 (combined with pytorch code)

Loss function comparison

[Loss function] SmoothL1Loss Smooth L1 loss function

Loss functions in target detection: IOU_Loss, GIOU_Loss, DIOU_Loss and CIOU_Loss

A detailed explanation and difference between L1 Regularization and L2 Regularization. It also explains in detail the function of regularization in the loss function and explains why regularization can prevent overfitting and improve generalization.

Target detection regression loss function IOU, GIOU, DIOU, CIOU, EIOU, Focal EIOU, alpha IOU loss function analysis

Loss Function - Perceptual Loss

Focal Loss loss function

Loss function (Loss)

mmsegmentation Add L1Loss

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